Ontological status of practice ​

The key concept of methodology is practice/activity/labor/engineering. This synonymous series can go on and on, for example, the term "work process" in modern management slang often means exactly "practice," but the concept of "method" and even "methodology" is the same. In English, there are also many analogous concepts: activity/action/practice/labor/engineering/method/way of working, and this series can also be continued. Definitions here are of little help, they usually capture only some aspect of practice and are not very suitable for grounding, for discovering practice in the world.

Practice represents the behavior of a functional object. People usually find it difficult to talk about behaviors/changes: it is hard to describe their boundaries, hard to find some common form of representation. Try to compare (find the commonalities and describe the differences), for example, the ballet performance "Swan Lake" and the world championship in Greco-Roman wrestling. And yet these are two examples of physical practices, it should be easier than comparing drilling wells at the bottom of the Pacific Ocean and producing Berber carpets in Morocco. And these are all examples of practices. A methodologist learns to look at the world primarily as changes in the world caused by agents/IPU — seeing practices in everything. This is not so simple: functional objects and their behavior/practices exist only when some constructive/physical objects play the role of performing services/work to change their environment. To see practice in the world, you need to:

• See many constructive/physical objects performing work. This means that you have taken the action of measurement: you first literally physically brought your senses into a situation in space-time where they can perceive various objects of the surrounding world directly or through some devices; then you perceived everything you could perceive with your senses and somehow highlighted from the background the important objects corresponding to some types. This means that you have a generative (able to produce the initial representation of the modeled world from a compressed/encoded internal representation, that is, to demodel) model and you, and the surrounding world, and you make hypotheses/guesses about the objects there, and then confirm them automatically intuitively or even invoke strict logical reasoning to make a reliable conclusion.
• Look at the situation for some time to notice changes caused by work. For this, concentration is needed (including collective): you (including many people and computers) have captured some objects with your attention and keep them, despite their movement, changes during interaction, the appearance of new objects, drifting attention to these new objects.
• Reflect on what is happening in terms of satisfying some activity/work/practical interest. This is the identification of a constructive object with a functional object. This is the moment when, hammering a nail, you recognize or a hammer or a stone — the object you see. The meaning of the situation emerges at this moment, although, in fact, it was present before: you already needed types of constructive objects at the previous step, and you could say something about the situation. But now you answer the question "why is this needed, what does it imply." This is a transition to the functional consideration. And it is extremely difficult. Functional object types are needed.
• All this happens in a situation of a severe lack of information. And your reasoning is active/proactive: you leave some of your "attention cameras" on these unidentified/unperceived constructive and functional objects and move yourself to examine-listen-feel the situation better, but you also google and read to have a better generative model of the world, have some expectations about the objects around you.
• The easiest thing here is to move from describing "behavior" to things: you simply list the objects that produce changes (creators that do not change themselves during interaction, changing work products, but sometimes these are mutual changes). But here, too, there is an obstacle: in fact, you are discussing cause-effect relationships: one functional object caused changes in another functional object ("the nail hit the nail, it transitioned from the state 'unhammered, lying in the box' to the state 'hammered where it should be up to the top hat,' the hammer::creator remained unchanged"). Cause-and-effect relationships are not so simple: a person sits and writes something on the computer because in the 21st century, people do not write on paper and not with a pen. Is the launch of a rocket to Mars a couple of years later the result of his writing, or not? Was he "just writing," or modeling a future flight, or giving orders? Ontological precise formal conversation becomes difficult, intuitions help, but not too much.

So, even just "observing" what happens during a practice turns out to be absolutely proactive "measurement," in which purely computational/thinking steps are closely intertwined with world and self-agent models and quite physical (and even with exotel, if it's about people, but it can also be a robot, which has continuous exotel) steps in changing the world. IPU (information processing units) turn out to be quite active, agents turn out to be quite computational, it's one and the same. And this reasoning is unlimited in scale! For instance, take such a creator as a stadium. Stadium::organization — is a robot that uses living employees in its composition (hybrot, he practices "entertainment": the advancement sub-practice (marketing, advertising, sales) encompasses inside 40,000 people, processes them internally for two hours, and then releases them satisfied. The stadium is a "creator/constructor": a physical object that can repeatedly perform homogeneous work with the surrounding world, but does not change itself (agent::physical object playing the role of actor/practice::functional object — the "homogeneity" of work performance means that all work corresponds to the same practice).

Thus, in fact, we equate thinking as an activity of knowing the world and changing the world as "simply activity": they happen simultaneously, it's the same thing. There is no thinking without changing the world and oneself. If there is no material in the physical world for thinking to lead to actions in changing the world — it is the same as not having "pure thinking" at all. Only the activity of obtaining data for computation and applying the results of computation to change the world counts, possibly following a long chain of reasoning and remembering intermediate results for several years. Moreover, all this is closely intertwined at multiple levels, because questions to the world and results of activity emerge not "at the very beginning of inference" and "at the very end of inference," but literally mixed together, in parallel.

This is a brief retelling of part of the content of the course of systems thinking, details and literature are indicated there.

Here we need to emphasize that practice is perceived as a combination of generative models of the world and oneself, these models are called the discipline of practice, as well as the instrumentation for measuring and changing the world, which is called technology. Discipline — is knowledge/"generative models of the world"/"explanatory theories". Technologies are the material support of discipline (the body of a dancer is his technology, and the discipline is his explanatory model of the world and himself, for example, the somatic mechanics discipline that we study in the courses of the systematic fitness, but in the dancer's technology, the floor covering can be added, which distinguishes rural dances from urban ones — on smooth urban floors, dance moves with "turns" in the legs are possible, while on village grounds, including asphalt surfaces, turns are only made "on steps," or else it will harm the knee ligaments). The technology of the practice of waging war turns out to be the whole country, so they try to destroy not only the military but also the country of that military to deprive the army of the opportunity to recover from losses, the sources of its supply of people and weapons disappear. The creators of high evolutionary levels skillfully restore their technology, as well as quickly develop their models of the world. It is poorly understood how this happens with humanity, societies, communities, but it is more or less clear with organizations and people.

Methodology as the teaching about the method (practice, labor, activity, as well as cognition, thinking, engineering, etc. — remembering that all this is one and the same) presupposes:

• You can operate with disciplines as explanatory theories (generative models of the world and oneself::agent/IPU) while conducting research (cognition/learning) or participating in the research of some community when the discipline is unclear, poorly defined, inaccurately models the world. You must at least guess to google to find out the current state of knowledge (SoTA) about this discipline if you are trying to understand some practice in the surrounding world. And you can conduct rational reasoning (obtain predictions of the states of the world and yourself-agent in case of some actions and choose the best actions depending on the riskiness and profitability of the action results). Research and rationality here are practices from the intellectual stack of fundamental disciplines. Fundamental disciplines can thus be defined as practices of working with practices, activities of working with activities, thinking of working with thinking! Fundamental disciplines are therefore practices of genuine learning, building models/theories, including models/theories of activity, among which we can include the activity/practice of cognition as the removal of uncertainty when encountering an unknown, poorly understood, contradictory world. Inference is thus part of cognition/learning, although it can be conducted independently based on a ready-made model if there is no inconsistency between the model's predictions and real life. If a discrepancy is detected — you need to switch to the cognition mode! And this discrepancy will always be there, so at the current level of technology development, people cannot be replaced by robots: robots do not switch to the learning mode at the slightest discrepancy between the results of their actions and the realities of the world! A person begins to think and solve the problem. This retells the concept of intelligence as the ability to quickly understand^, and this text does not emphasize the active nature of cognition/thinking, only the "computational" part is discussed. mоre. At the same time, learning/inquiry/thinking/learning is arranged similarly when the agent directly faces the world and during learning from textbooks or with a teacher (one has to make guesses/hypotheses and confirm them with reasoning and practical experiments both in the first and in the second case, building a concept in their individual or even collective calculator based on some externally observable phenomena: or ongoing events or read textbooks).
• You can define which objects of the physical world in which designs (that is, which functional objects) constitute the technology of practice. This is also a reference to your ability to know the world, find some objects in it. Working with technology happens through practices, they also imply changes in the world (even when actively observing-measuring, it is still active!), and also include working with models of these technologies, also require intelligence.

Practices are well decomposed:

• Role/functional objects are well decomposed (system breakdown) both in the case of work products and in the case of creators (who change the state of the work products, however, they themselves can be work products, there are chains of creation). And practices are also decomposed. Although it is not guaranteed that only one role is engaged in practice: the practice of buying-selling involves the roles of the seller, buyer, payer, payment recipient/cashier, beneficiary, etc.
• Physical objects that will perform these roles in practices are well decomposed (part-whole relationships, but remember that this breakdown is not entirely arbitrary, it is advisable to distinguish such parts that are stable in the surrounding world. The cup has fused molecules that do not diverge anywhere for several years, and you can somehow draw the boundary between the cup molecules and the rest of the world, however, the "cup half" will not be as clearly defined in the physical world, the molecules of half a cup cannot be clearly sorted during measurement, cannot be moved independently, cannot be made independently, cannot interact with these pieces independently — that's why we carefully identify physical objects).
• How models/disciplines of practice are decomposed — is a very complex issue. The relationship of part-whole on mathematical objects is not defined. Especially since there are always fundamental disciplines that implicitly enter into all applied practices and are activated when the real situation does not correspond to the expectations generated from the explanatory models of the practice discipline. Fundamental disciplines are sometimes also called transdisciplines, "beyond disciplines". In the division of disciplines today, we mainly rely on a circle of vision, there are no special principles here: people still distinguish mathematics as a discipline from biomechanics, and biomechanics after certain explanations from somatomachanics. The same applies to methodology, ontology, theory of concepts, and other fundamental disciplines: they are significantly intertwined, and there is no consensus on how their subjects of study are delimited.

Metanoia, which the methodologist should receive is to look at the agents acting in the world (IPU/constructor: beings, people, organizations, etc.) and somehow identify the practice in which this agent is engaged, his level of qualification in this practice, how up-to-date is this practice (how SoTA the discipline/theory, how SoTA technology is), how strong the intelligence of the agent is (i.e. what will happen when something goes wrong during the practice "something goes wrong"). This thinking is the same when you think about your cat, your employees, the organization you deal with. Carefully (there are not yet many good predictive knowledge/theories and methodologies on these levels, methodology before rarely looked at them, focusing more on people), but this thinking can also be applied to communities and even societies — but they are not physical objects and are difficult to think about (although recently there are ways to do this, here you can refer to the constructivist understanding of building a whole from parts proposed by Kit Fine, but also reasoning that dealing with communities is less about the community itself and its structure, but more about the activity situations in whcih the members of the community are involved in some role — for instance, a community of accountants is engaged in accounting activities in certain projects, and it is these projects and this activity that will be the focus of the discussion about the community, and not the organization of the community itself and its architecture). Therefore, be more cautious with communities and especially societies, but you will have to do this if you engage in areas like marketing, education, or political activity.

All this is well decomposed, modern methodology is systemic: it works with hierarchies of practices (which are broken down according to part-whole relations of their technologies, including agents, tools/equipment, work products) as well as with hierarchies of target objects of these practices. Thus, methodological thinking is multi-level/scale-free.

So when you think about practices, you distinguish and use in reasoning objects of the following types:

• Method/practice/activity/engineering/labor (and many other synonyms, they should not overshadow the concepts)
• Role of the practicing agent
• Discipline/theory (explanatory) of practice
• Technology of practice
• Thinking based on fundamental disciplines of the intellectual stack, as active reasoning during cognition (research or learning), it manifests itself when works on the practice lead to unexpected results (at the same time, we do not consider time: do we foresee in advance that the result will be surprising and plan ahead or discover during work or even after completing work, that we obtained unexpected results. Thinking works fine with the future, it is based on generative models that can generate images of this future and assess their probability rationally, assess the consequences of actions rationally)